Orthogonal frequency division multiplexing (OFDM) is a multi-carrier communication scheme in which, data at a high rate is divided into sub-streams and transmitted over orthogonal carriers, thus enabling data transmission over a frequency selective fading channel, in a bandwidth efficient manner.
Channel estimation is an important constituent of coherent OFDM receivers. Guard intervals are inserted between adjacent OFDM block symbols, to take care of Inter Block Interference (IBI). Transmitting a Cyclic Prefix (CP) of the data during this interval makes the channel circularly convolutive, simplifying the channel equalization problem. Specifically, channel equalization in the frequency domain can be done using one tap filters. This is because the CP makes the channel matrix circulant, which is diagonalized by the inverse discrete Fourier transform (IDFT) and DFT operations. The challenge in frequency domain channel equalization lies in estimating the channel frequency coefficients at all the subcarriers.
In conventional OFDM systems, channel estimation is done using pilot tones along with data. In slow fading environments, channel estimation can be done by inserting pilot tones into all of the subcarriers of the OFDM symbol with a specific period during which the channel is assumed to be quasi-static. In fast fading environments pilot tones are inserted at specific subcarriers in each OFDM symbol. The channel frequency coefficients at the data tones are then determined by interpolation based approximations resulting in channel estimation errors, which could be significant in a frequency selective fading channel. Also, pilot tone insertion reduces the bandwidth efficiency of the system. The need for higher data rates and mobility only aggravates the problem. This motivates the need for blind estimators which exploits the statistics of the transmitted data, or some redundancy in the transmitted data to estimate the channel without employing pilots. Traditionally blind estimators have been found to have a slow convergence time and also there is a possibility of convergence of the performance surface to a local minimum. Semi-blind equalization allows for a trade-off between performance and bandwidth efficiency by making use of blind as well as pilot assisted techniques.
“Channel estimation with superimposed pilot sequence,” Proceedings of the IEEE-GLOBECOM, vol. 4, pp. 2162-2166, December 1999, by Hoeher P and Tufvesson F, discloses a superimposed pilot training sequence technique for the purpose of channel estimation in a coherent receiver based on the Viterbi algorithm for single carrier systems.
“Channel estimation and equalization for M-QAM Transmission with a hidden pilot sequence,” IEEE Transactions on Broadcasting, vol. 48, no. 2, pp. 170-176, June 2000 by F. Mazzenga discloses a method for estimating the channel by preserving the bandwidth efficiency at the expense of increasing the transmitted power and using a known pilot sequence hidden into the informative sequence.
“A Simultaneous Information Transfer and Channel-Sounding Modulation Technique for Wide-Band Channels,” IEEE Transactions on Communications, June 1965, vol 13 no: 2, pp-162-165, by Kastenholz and Birkmeier, discloses a method of superimposing a pseudorandom channel sounding signal by amplitude modulation upon a conventional FM information-bearing signal.
“Channel estimation using implicit training,” IEEE Transactions on Signal Processing, vol. 52, no. 1, January 2004 by A. G. Orozco-Lugo, M. Lara, D. Mc Lernon discloses a new method to perform channel estimation. It is shown that accurate estimation can be obtained when a training sequence is actually arithmetically added to the information data as opposed to being placed in a separate empty time slot.
The article “Superimposed Training for OFDM: a peak-to-average power ratio analysis,” IEEE Transactions on Signal Processing, vol. 54, no. 6, pp. 2277-2287, June 2006 by N. Chen and G. T. Zhou describes an orthogonal frequency division multiplexing (OFDM) transmission with superimposed training. The PAR of the OFDM signal is examined with superimposed training, and its complementary cumulative distribution function (CCDF) is derived. Achievable lower and upper bounds on the CCDF are also determined. In addition, the PAR change is linked to the effective signal-to-noise ratio (SNR) and thus the bit-error-rate (BER) performance under the fixed dc power constraint.
The article Proceedings of the IEEE-GLOBECOM, vol. 2, no. 2, pp. 878-882, December 2003 by N. Ohkubo and T. Ohtsuki teaches added pilot semi-blind channel estimation for OFDM packet transmission.
ETRI Journal, vol. 28, no. 5, pp. 688-691, October 2006 by Q. Yang and K. S. Kwak teaches “Time-varying multipath channel estimation with superimposed training in CP-OFDM systems”. A time-domain channel estimation scheme for time-varying multipath channels is developed by using superimposed sequences. The idea behind this scheme is to split the one-OFDM-symbol-period time-domain channel into equi-spaced time-slotted sub channels, so that the time variation for each sub channel can be assumed to be negligible; then, each sub channel is estimated by a linear least square (LS) estimator.
The article Proceedings of the IEEE-GLOBECOM, Missouri, USA, December 2005, pp. 2229-2233T by Cui and C. Tellambura discloses “Superimposed pilot symbols for channel estimation in OFDM systems”. Article Proceedings of the IEEE-GLOBECOM, Texas, USA, November 2001, 3075-3079 by C. K. Ho, B. Farhang-Boroujeny and F. Chin discloses “Added pilot semi-blind channel estimation scheme for OFDM in fading channels”. Article IEEE Communications Letters, vol. 7, no. 1, pp. 30-32, January 2003 by H. Zhu, B. Farhang-Boroujeny and C. Schlegel teaches “Pilot embedding for joint channel estimation and data detection in MIMO communication systems”. Further the article Proceedings of the IEEE-GLOBECOM, Dallas, USA, November 2004, pp. 1244-1248 by S. Balasubramanian, B. Farhang-Boroujeny and V. John Mathews describes “Pilot embedding for channel estimation and tracking in OFDM systems”.
There is a need for bandwidth efficient channel estimation techniques for OFDM with good performance. Recently, superimposed training (ST) based channel estimation techniques have been proposed. In this scheme, training symbols known to the receiver are algebraically added on to the data at a low power, thus avoiding the need for additional time slots for training. At the receiver these known symbols, in the presence of unknown data and noise, are exploited for channel estimation. These methods for channel estimation are attractive compared to pilot assisted techniques as they are bandwidth efficient. ST based methods for channel estimation in OFDM have been considered in the literature for use in present and future generation cellular including 4G, the focus being on iterative source channel estimation techniques, the optimality criteria for the training sequences and peak to average power (PAPR) analysis.
The state of the art however, leaves many critical issues unanswered. Iterative channel estimation techniques to get improved accuracy and also to further reduce the interference of the data on the estimate are used. However the LS channel estimate used does not exploit the nature of the frequency selective block fading channel that occurs in practice. The ST sequence used for channel estimation plays a pivotal role in system performance. The cost function that is used to characterize the optimal training sequences is the minimization of the mean square estimation error (MSEE) or the Cramer-Rao lower bound (CRLB). These are also the optimization criteria generally used for pilot assisted techniques which are reasonable because in this case the training is separated from the data. However, in the superimposed training scheme both of these criteria result in characterizations that does not take into account the interference of the training sequences on the data detection. Moreover the training sequences used in the existing art will not be applicable in currently standardized wireless OFDM systems because of the existence of frequency components at the band edges which are generally used in the brick wall shaping of the transmit spectrum. It was not known in the prior art of using superimposed training that the number of OFDM symbols experiencing the same channel may be used to improve the channel estimation accuracy by averaging over several symbols depending on the coherence time of the channel and/or the desired estimation accuracy. Hence the number of OFDM symbols averaged to estimate the channel impulse response making it suitable to the characteristics of the channel encountered in different standards by the superimposed training based OFDM system was not in the prior art.
Thus there is a need to provide for a system and method for jointly minimizing the mean square estimation error (MSEE) and bit error rate (BER) during channel estimation and equalization in orthogonal frequency division multiplexing (OFDM) systems.
Thus in a quest for obtaining an optimal equalizer, the present inventors have got a new idea and found that channel MSEE and the BER can be jointly minimized thereby arrived at a digitized linear frequency modulation (LFM) based optimal training sequence that fairly distributes the interference due to the training on the data on all the used sub-carriers for superimposed training based OFDM systems and further introduced averaging of the channel estimates beyond one OFDM symbol so as to obtain an improved channel estimation from OFDM symbols experiencing the same fading coefficients. This improves channel estimation in OFDM systems without using additional bandwidth for the purpose of channel estimation and equalization.